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通过并行计算驾驭生物途径的复杂性。

Taming the complexity of biological pathways through parallel computing.

作者信息

Ballarini Paolo, Guido Rosita, Mazza Tommaso, Prandi Davide

机构信息

The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manci 17 38100 Povo, Trento, Italy.

出版信息

Brief Bioinform. 2009 May;10(3):278-88. doi: 10.1093/bib/bbp020. Epub 2009 Apr 1.

Abstract

Biological systems are characterised by a large number of interacting entities whose dynamics is described by a number of reaction equations. Mathematical methods for modelling biological systems are mostly based on a centralised solution approach: the modelled system is described as a whole and the solution technique, normally the integration of a system of ordinary differential equations (ODEs) or the simulation of a stochastic model, is commonly computed in a centralised fashion. In recent times, research efforts moved towards the definition of parallel/distributed algorithms as a means to tackle the complexity of biological models analysis. In this article, we present a survey on the progresses of such parallelisation efforts describing the most promising results so far obtained.

摘要

生物系统的特点是有大量相互作用的实体,其动态过程由许多反应方程来描述。用于对生物系统进行建模的数学方法大多基于集中式求解方法:将被建模系统作为一个整体来描述,并且通常以集中式方式计算求解技术,通常是常微分方程组(ODEs)的积分或随机模型的模拟。近年来,研究工作朝着定义并行/分布式算法的方向发展,以此作为应对生物模型分析复杂性的一种手段。在本文中,我们对这种并行化工作的进展进行了综述,描述了目前已取得的最有前景的成果。

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